Browsing by Author "Tsuie, YM"

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A constrained decision feedback equalizer for reduced complexity maximum likelihood sequence estimation
(2002-01-01)
Wu, WR
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Tsuie, YM
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電信工程研究所
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Institute of Communications Engineering
The maximum likelihood sequence estimator (MLSE) is usually implemented by the Viterbi algorithm (VA). The computational complexity of the VA grows exponentially with the length of the channel response. With some performance reduction, a decision-feedback equalizer (DFE) can be used to shorten the channel response. This greatly reduces the computational requirement for the VA. However, for many real-world applications, the complexity of the DFE/MLSE approach may be still too high. In this paper, we propose, a constrained DFE that offers much lower VA computational complexity. The basic idea is to pose some constraints on the DFE such that the postcursors of the, shortened channel response have only discrete values. As a result, the multiplication operations can be replaced by shift operations making the VA almost multiplication free. This will greatly facilitate the real world applications of the MLSE algorithm. Simulation results show that while the proposed algorithm basically offers the same performance as the original MLSE performance, the VA is much more efficient than the conventional approach.
An LMS-based decision feedback equalizer for digital cellular radio
(1996)
Wu, WR
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Tsuie, YM
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交大名義發表
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傳播研究所
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National Chiao Tung University
In a TDMA mobile communication system, the equalizer is a common device to compensate the intersymbol interference caused by the multipath effect. In this paper, we consider the decision feedback equalizer (DFE) for application to the North American IS-54 systems. Due to the fast fading characteristic of channels, most conventional DFEs use the recursive least square (RLS) algorithm. However, it is known that the RLS algorithm is computationally intensive and not easy to implement. In this paper, we employ the ideas of multiple-training and multiple-tracking to propose an LMS-based equalization scheme. We also incorporate the Coded Digital Verification Color Code (CDVCC) of the TDMA slot as an additional training sequence. Simulation results show that the new scheme can achieve a bit error rate of 3% at the mobile speed of 80km/hr and still remains a low complexity.
An LMS-based decision feedback equalizer for IS-136 receivers
(2002-01-01)
Wu, WR
;
Tsuie, YM
;
電信工程研究所
;
Institute of Communications Engineering
In digital mobile communication systems, inter-symbol interference is one of the main causes of degrading system performance. Decision feedback equalization (DFE) is the commonly used remedy for this problem. Since the channel is fast-varying, an adaptive algorithm possessing a fast convergence property is then required. The least mean square (LMS) algorithm is well known for its simplicity and robustness; however, its convergence is slow. As a consequence, the LMS algorithm is rarely considered in this application. In this paper, we consider an LMS-based DFE for the North American IS-136 system. We propose an extended multiple-training LMS algorithm accelerating the convergence process. The convergence properties of the multiple-training LMS algorithm are also analyzed. We prove that the multiple-training LMS algorithm can converge regardless of its initial value and derive closed-form expressions for the weight error vector power. We further take advantage of the IS-136 downlink slot format and divide a slot into two subslots. Bidirectional processing is then applied to each individual subslot. The proposed LMS-based DFE has a low computational complexity and is suitable for real-world implementation. Simulations with a 900- MHz carrier show that our algorithm can meet the 3% bit error rate requirement for mobile speeds up to 100 km/hr.
Error probability analysis for adaptive decision feedback equalizers under slowly fading multipath channels
(2001)
Tsuie, YM
;
Wu, WR
;
電信工程研究所
;
Institute of Communications Engineering
It is very difficult to analyze the error probability of the adaptive decision feedback equalizer (DFE) when it is operated under a time-varying channel. A decision error not only propagates through the feedback filter affecting the future outputs, but also through the adaptive algorithm updating the tap weights toward a wrong direction. Most of the existing analysis works do not consider the error propagation effect in the adaptive algorithm. In this paper, we specifically take this effect into account and analyze the error probability of the DFE under the slowly fading channels. We consider the most widely used adaptive algorithm, namely, the least mean square (LMS) algorithm. Closed-form expressions are derived for the training mode as well as the decision-directed mode. Finally, the validity of the theoretical results are verified through computer simulations.